As is known in the art, cloud computing systems contain a large number of hardware devices, components, software applications, and modules. For example, cloud computing systems can include integrated compute, network, and storage domains. In typical systems, redundancy is built into each domain to ensure services are not disrupted because of hardware failures. For example, two fabrics and two switches provide multiple paths for each server blade to get to network or storage resources. In the storage domain, RAID technology with hot spare disks prevents data loss due to disk failures.
Traditionally, the redundancy on a group of resources has been measured using a fractional threshold, e.g., 2 out of 4 links are down. One example of using this method is the analytic model in the EMC ITOI SMARTS domain manager. In other known systems, redundancy is classified into categories, such as redundancy lost, redundancy degraded, etc., based on the number of available resources. A classification of this type appears in some VMware vCenter events such as storage path redundancy events. Some conventional systems use analytics that measure risk by predicting the headroom in terms of capacity. This technology is being used in the VMware Capacity IQ, for example. However, this concerns a different aspect of resources, namely, capacity, but not redundancy or availability.